> Our hands are a marvel of evolution allowing us to do extremely precise tasks while still being adaptable to all kind of movement

It's easy to overlook, but to me it's amazing that humans are able to type! Subtle, precise movements by our fingers to express language were presumably not skills our ancestors had an evolutionary advantage for.

Very cool! Can you say a little bit about the size of the DPO training examples and how long training took?

For DPO I only had around 700 preference examples, so not much data at all. That took about 12 minutes to train on a single GPU.

Pretraining was obviously a a lot slower, the 125M model took roughly half a day.

"Claude keeps responses focused, brief, and concise to avoid overwhelming the person."

Claude and I must have a different idea of what brief and concise mean.

The model almost certainly lacks accurate conceptions of overwhelming and person.

If you think Claude is bad at this, try Gemini. Even with explicit user prompts.

Claude seems to be better (not good, but significantly better) at judging where making the answer longer will actually be helpful (e.g. adding important information/context/nuance that a short answer would miss, thinking a step ahead, etc.).

Interesting, they say "focused, brief, and concise" but not "clear". I find the Claude responses these days are too dense, which contributes to being overwhelming. It's not the number of words used that overwhelm me. I've been asking it to use ASD-STE100 and that helps somewhat.

very much this

dense and often somehow 'ungrounded' from my perspective... like it doesn't understand the need to bring me up to speed with what we're talking about before stating it

It feels a bit like some of the style of internal reasoning (dense, shorthand jargon) is leaking into its responses to me

Imagine what it's like without that line.

Since reasoning tokens are just text, I think the models have learned to squeeze in some computation in their output writing as well. So they're incentivized to be correct but long-winded, as it gives them more time to think. It's kind of the equivalent of filler words for humans, except LLMs can actually word-vomit something intelligible.

Right, but could that also be because ... the more long-winded they are, the more you pay for their output.

I'd also be really curious about the cost to run something like this, and what things you think it's particularly helpful for?

I run this on a side of the Claude Pro subscription that I use for other purposes. My main motivation was root cause analysis of production issues. I have a solo project and unfortunately my mental state has been degrading over the last years. I would avoid looking at production issues, because I didn't have the energy to focus on the investigation. So I automated this, setup the loop, setup metrics/logs access for Claude to use and now whenever something goes bad, I have a single report that I can act on easily, and if I don't, it will ping me in a way that's not spammy like automated alerts. But I'm finding more uses for it.

Building a simple sandboxed way to run open weight models over a copy of all my personal data (email, docs, messaging, photos, etc). Think it'd be cool to have a self hosted AI "chief of staff" that has full read access to my personal info.